code: def _upload_to_gcp_storage(exec_dir):
      """Upload all files to GCP storage under exec_dir folder.
  
      Args:
          exec_dir (str): The execution directory.
  
      """
      _bucket = storage.Client().bucket("resl-garage-benchmarks")
      exec_name = os.path.basename(exec_dir)
  
      for folder_name in os.listdir(exec_dir):
          folder_path = os.path.join(exec_dir, folder_name)
          if not os.path.isfile(folder_path):
              remote_folder = os.path.join(exec_name, folder_name)
  
              for file_name in os.listdir(folder_path):
                  file_path = os.path.join(folder_path, file_name)
                  if os.path.isfile(file_path):
                      blob = _bucket.blob(
                          os.path.join(remote_folder, file_name)
                      )
                      blob.upload_from_filename(file_path)
  
file_path: garage/benchmarks/src/garage_benchmarks/helper.py
imports: import csv
  import functools
  import json
  import os
  import pathlib
  import random
  import subprocess
  from google.cloud import storage
  import matplotlib.pyplot
  import numpy
  import tensorflow
label_desc: Use image node_id 7 for calling a global function with example usage: _upload_to_gcp_storage(exec_dir) without return types